{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## User Exploration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There were 213451 users in the training set and 62096 in the test set.\n",
      "In total there were 275547 users.\n"
     ]
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "train_users = pd.read_csv('train_users_2.csv')\n",
    "test_users = pd.read_csv('test_users.csv')\n",
    "print(\"There were\", train_users.shape[0], \"users in the training set and\", test_users.shape[0], \"in the test set.\")\n",
    "print(\"In total there were\", train_users.shape[0] + test_users.shape[0], \"users.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.concat((train_users, test_users), axis=0, ignore_index=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Missing Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "affiliate_channel               0\n",
       "affiliate_provider              0\n",
       "age                        116866\n",
       "country_destination         62096\n",
       "date_account_created            0\n",
       "date_first_booking         186639\n",
       "first_affiliate_tracked      6085\n",
       "first_browser                   0\n",
       "first_device_type               0\n",
       "gender                          0\n",
       "id                              0\n",
       "language                        0\n",
       "signup_app                      0\n",
       "signup_flow                     0\n",
       "signup_method                   0\n",
       "timestamp_first_active          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>affiliate_channel</th>\n",
       "      <th>affiliate_provider</th>\n",
       "      <th>age</th>\n",
       "      <th>country_destination</th>\n",
       "      <th>date_account_created</th>\n",
       "      <th>date_first_booking</th>\n",
       "      <th>first_affiliate_tracked</th>\n",
       "      <th>first_browser</th>\n",
       "      <th>first_device_type</th>\n",
       "      <th>gender</th>\n",
       "      <th>id</th>\n",
       "      <th>language</th>\n",
       "      <th>signup_app</th>\n",
       "      <th>signup_flow</th>\n",
       "      <th>signup_method</th>\n",
       "      <th>timestamp_first_active</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NDF</td>\n",
       "      <td>2010-06-28</td>\n",
       "      <td>NaN</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>-unknown-</td>\n",
       "      <td>gxn3p5htnn</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>facebook</td>\n",
       "      <td>20090319043255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>seo</td>\n",
       "      <td>google</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NDF</td>\n",
       "      <td>2011-05-25</td>\n",
       "      <td>NaN</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>MALE</td>\n",
       "      <td>820tgsjxq7</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>facebook</td>\n",
       "      <td>20090523174809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>56.0</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-09-28</td>\n",
       "      <td>2010-08-02</td>\n",
       "      <td>untracked</td>\n",
       "      <td>IE</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>4ft3gnwmtx</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>3</td>\n",
       "      <td>basic</td>\n",
       "      <td>20090609231247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>42.0</td>\n",
       "      <td>other</td>\n",
       "      <td>2011-12-05</td>\n",
       "      <td>2012-09-08</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Firefox</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>bjjt8pjhuk</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>facebook</td>\n",
       "      <td>20091031060129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>41.0</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-09-14</td>\n",
       "      <td>2010-02-18</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>-unknown-</td>\n",
       "      <td>87mebub9p4</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>basic</td>\n",
       "      <td>20091208061105</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>other</td>\n",
       "      <td>other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>2010-01-02</td>\n",
       "      <td>omg</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>-unknown-</td>\n",
       "      <td>osr2jwljor</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>basic</td>\n",
       "      <td>20100101215619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>other</td>\n",
       "      <td>craigslist</td>\n",
       "      <td>46.0</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-01-02</td>\n",
       "      <td>2010-01-05</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Safari</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>lsw9q7uk0j</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>basic</td>\n",
       "      <td>20100102012558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>47.0</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-01-03</td>\n",
       "      <td>2010-01-13</td>\n",
       "      <td>omg</td>\n",
       "      <td>Safari</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>0d01nltbrs</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>basic</td>\n",
       "      <td>20100103191905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>other</td>\n",
       "      <td>craigslist</td>\n",
       "      <td>50.0</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>2010-07-29</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Safari</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>a1vcnhxeij</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>basic</td>\n",
       "      <td>20100104004211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>other</td>\n",
       "      <td>craigslist</td>\n",
       "      <td>46.0</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>2010-01-04</td>\n",
       "      <td>omg</td>\n",
       "      <td>Firefox</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>-unknown-</td>\n",
       "      <td>6uh8zyj2gn</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>basic</td>\n",
       "      <td>20100104023758</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  affiliate_channel affiliate_provider   age country_destination  \\\n",
       "0            direct             direct   NaN                 NDF   \n",
       "1               seo             google  38.0                 NDF   \n",
       "2            direct             direct  56.0                  US   \n",
       "3            direct             direct  42.0               other   \n",
       "4            direct             direct  41.0                  US   \n",
       "5             other              other   NaN                  US   \n",
       "6             other         craigslist  46.0                  US   \n",
       "7            direct             direct  47.0                  US   \n",
       "8             other         craigslist  50.0                  US   \n",
       "9             other         craigslist  46.0                  US   \n",
       "\n",
       "  date_account_created date_first_booking first_affiliate_tracked  \\\n",
       "0           2010-06-28                NaN               untracked   \n",
       "1           2011-05-25                NaN               untracked   \n",
       "2           2010-09-28         2010-08-02               untracked   \n",
       "3           2011-12-05         2012-09-08               untracked   \n",
       "4           2010-09-14         2010-02-18               untracked   \n",
       "5           2010-01-01         2010-01-02                     omg   \n",
       "6           2010-01-02         2010-01-05               untracked   \n",
       "7           2010-01-03         2010-01-13                     omg   \n",
       "8           2010-01-04         2010-07-29               untracked   \n",
       "9           2010-01-04         2010-01-04                     omg   \n",
       "\n",
       "  first_browser first_device_type     gender          id language signup_app  \\\n",
       "0        Chrome       Mac Desktop  -unknown-  gxn3p5htnn       en        Web   \n",
       "1        Chrome       Mac Desktop       MALE  820tgsjxq7       en        Web   \n",
       "2            IE   Windows Desktop     FEMALE  4ft3gnwmtx       en        Web   \n",
       "3       Firefox       Mac Desktop     FEMALE  bjjt8pjhuk       en        Web   \n",
       "4        Chrome       Mac Desktop  -unknown-  87mebub9p4       en        Web   \n",
       "5        Chrome       Mac Desktop  -unknown-  osr2jwljor       en        Web   \n",
       "6        Safari       Mac Desktop     FEMALE  lsw9q7uk0j       en        Web   \n",
       "7        Safari       Mac Desktop     FEMALE  0d01nltbrs       en        Web   \n",
       "8        Safari       Mac Desktop     FEMALE  a1vcnhxeij       en        Web   \n",
       "9       Firefox       Mac Desktop  -unknown-  6uh8zyj2gn       en        Web   \n",
       "\n",
       "   signup_flow signup_method  timestamp_first_active  \n",
       "0            0      facebook          20090319043255  \n",
       "1            0      facebook          20090523174809  \n",
       "2            3         basic          20090609231247  \n",
       "3            0      facebook          20091031060129  \n",
       "4            0         basic          20091208061105  \n",
       "5            0         basic          20100101215619  \n",
       "6            0         basic          20100102012558  \n",
       "7            0         basic          20100103191905  \n",
       "8            0         basic          20100104004211  \n",
       "9            0         basic          20100104023758  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array(['-unknown-', 'MALE', 'FEMALE', 'OTHER'], dtype=object),\n",
       " array(['Chrome', 'IE', 'Firefox', 'Safari', '-unknown-', 'Mobile Safari',\n",
       "        'Chrome Mobile', 'RockMelt', 'Chromium', 'Android Browser',\n",
       "        'AOL Explorer', 'Palm Pre web browser', 'Mobile Firefox', 'Opera',\n",
       "        'TenFourFox', 'IE Mobile', 'Apple Mail', 'Silk', 'Camino', 'Arora',\n",
       "        'BlackBerry Browser', 'SeaMonkey', 'Iron', 'Sogou Explorer',\n",
       "        'IceWeasel', 'Opera Mini', 'SiteKiosk', 'Maxthon',\n",
       "        'Kindle Browser', 'CoolNovo', 'Conkeror', 'wOSBrowser',\n",
       "        'Google Earth', 'Crazy Browser', 'Mozilla', 'OmniWeb',\n",
       "        'PS Vita browser', 'NetNewsWire', 'CometBird', 'Comodo Dragon',\n",
       "        'Flock', 'Pale Moon', 'Avant Browser', 'Opera Mobile',\n",
       "        'Yandex.Browser', 'TheWorld Browser', 'SlimBrowser', 'Epic',\n",
       "        'Stainless', 'Googlebot', 'Outlook 2007', 'IceDragon', 'IBrowse',\n",
       "        'Nintendo Browser', 'UC Browser'], dtype=object))"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['gender'].unique(), df['first_browser'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.gender.replace('-unknown-', np.nan, inplace=True)\n",
    "df.first_browser.replace('-unknown-', np.nan, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "affiliate_channel               0\n",
       "affiliate_provider              0\n",
       "age                        116866\n",
       "country_destination         62096\n",
       "date_account_created            0\n",
       "date_first_booking         186639\n",
       "first_affiliate_tracked      6085\n",
       "first_browser               44394\n",
       "first_device_type               0\n",
       "gender                     129480\n",
       "id                              0\n",
       "language                        0\n",
       "signup_app                      0\n",
       "signup_flow                     0\n",
       "signup_method                   0\n",
       "timestamp_first_active          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.drop('date_first_booking', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "affiliate_channel               0\n",
       "affiliate_provider              0\n",
       "age                        116866\n",
       "country_destination         62096\n",
       "date_account_created            0\n",
       "first_affiliate_tracked      6085\n",
       "first_browser               44394\n",
       "first_device_type               0\n",
       "gender                     129480\n",
       "id                              0\n",
       "language                        0\n",
       "signup_app                      0\n",
       "signup_flow                     0\n",
       "signup_method                   0\n",
       "timestamp_first_active          0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.isnull().sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Users' Age"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    158681.000000\n",
       "mean         47.145310\n",
       "std         142.629468\n",
       "min           1.000000\n",
       "25%          28.000000\n",
       "50%          33.000000\n",
       "75%          42.000000\n",
       "max        2014.000000\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.age.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The maximum age is 2014, this is not possible. It seems that some users have filled a year instead of their age. Also the minimun age at 1 sounds rediculous. According to Airbnb's contract, users at the platform must be at least 18 years old. However, this is not enforced. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count     828.000000\n",
       "mean     2007.117150\n",
       "std        22.219408\n",
       "min      1920.000000\n",
       "25%      2014.000000\n",
       "50%      2014.000000\n",
       "75%      2014.000000\n",
       "max      2014.000000\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['age'] > 1000]['age'].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    188.000000\n",
       "mean      12.718085\n",
       "std        5.764569\n",
       "min        1.000000\n",
       "25%        5.000000\n",
       "50%       16.000000\n",
       "75%       17.000000\n",
       "max       17.000000\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.loc[df['age'] < 18]['age'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "So we will first correct every mistakenly filled the age."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_with_year = df['age'] > 1000\n",
    "df.loc[df_with_year, 'age'] = 2015 - df.loc[df_with_year, 'age']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    158681.000000\n",
       "mean         36.713274\n",
       "std          14.046364\n",
       "min           1.000000\n",
       "25%          28.000000\n",
       "50%          33.000000\n",
       "75%          42.000000\n",
       "max         150.000000\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.age.describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "After that, the Minimum age at 1 and Maximum age at 150 were not realistic, we will set limit for the age, and set nan for outliers. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.loc[df.age > 95, 'age'] = np.nan\n",
    "df.loc[df.age < 16, 'age'] = np.nan"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    155887.000000\n",
       "mean         36.033370\n",
       "std          11.589997\n",
       "min          16.000000\n",
       "25%          28.000000\n",
       "50%          33.000000\n",
       "75%          42.000000\n",
       "max          95.000000\n",
       "Name: age, dtype: float64"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['age'].describe()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks more reasonable. We can now visualize the age."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SusanLi\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\scipy\\stats\\stats.py:1713: FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`. In the future this will be interpreted as an array index, `arr[np.array(seq)]`, which will result either in an error or a different result.\n",
      "  return np.add.reduce(sorted[indexer] * weights, axis=axis) / sumval\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x176814905f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.distplot(df.age.dropna(), rug=True)\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As expected, the most common age of Airbnb users is between 25 and 40."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Users' Gender"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>affiliate_channel</th>\n",
       "      <th>affiliate_provider</th>\n",
       "      <th>age</th>\n",
       "      <th>country_destination</th>\n",
       "      <th>date_account_created</th>\n",
       "      <th>first_affiliate_tracked</th>\n",
       "      <th>first_browser</th>\n",
       "      <th>first_device_type</th>\n",
       "      <th>gender</th>\n",
       "      <th>id</th>\n",
       "      <th>language</th>\n",
       "      <th>signup_app</th>\n",
       "      <th>signup_flow</th>\n",
       "      <th>signup_method</th>\n",
       "      <th>timestamp_first_active</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NDF</td>\n",
       "      <td>2010-06-28</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>NaN</td>\n",
       "      <td>gxn3p5htnn</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>facebook</td>\n",
       "      <td>20090319043255</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>seo</td>\n",
       "      <td>google</td>\n",
       "      <td>38.0</td>\n",
       "      <td>NDF</td>\n",
       "      <td>2011-05-25</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>MALE</td>\n",
       "      <td>820tgsjxq7</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>facebook</td>\n",
       "      <td>20090523174809</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>56.0</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-09-28</td>\n",
       "      <td>untracked</td>\n",
       "      <td>IE</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>4ft3gnwmtx</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>3</td>\n",
       "      <td>basic</td>\n",
       "      <td>20090609231247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>42.0</td>\n",
       "      <td>other</td>\n",
       "      <td>2011-12-05</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Firefox</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>bjjt8pjhuk</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>facebook</td>\n",
       "      <td>20091031060129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>41.0</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-09-14</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>NaN</td>\n",
       "      <td>87mebub9p4</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>basic</td>\n",
       "      <td>20091208061105</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  affiliate_channel affiliate_provider   age country_destination  \\\n",
       "0            direct             direct   NaN                 NDF   \n",
       "1               seo             google  38.0                 NDF   \n",
       "2            direct             direct  56.0                  US   \n",
       "3            direct             direct  42.0               other   \n",
       "4            direct             direct  41.0                  US   \n",
       "\n",
       "  date_account_created first_affiliate_tracked first_browser  \\\n",
       "0           2010-06-28               untracked        Chrome   \n",
       "1           2011-05-25               untracked        Chrome   \n",
       "2           2010-09-28               untracked            IE   \n",
       "3           2011-12-05               untracked       Firefox   \n",
       "4           2010-09-14               untracked        Chrome   \n",
       "\n",
       "  first_device_type  gender          id language signup_app  signup_flow  \\\n",
       "0       Mac Desktop     NaN  gxn3p5htnn       en        Web            0   \n",
       "1       Mac Desktop    MALE  820tgsjxq7       en        Web            0   \n",
       "2   Windows Desktop  FEMALE  4ft3gnwmtx       en        Web            3   \n",
       "3       Mac Desktop  FEMALE  bjjt8pjhuk       en        Web            0   \n",
       "4       Mac Desktop     NaN  87mebub9p4       en        Web            0   \n",
       "\n",
       "  signup_method  timestamp_first_active  \n",
       "0      facebook          20090319043255  \n",
       "1      facebook          20090523174809  \n",
       "2         basic          20090609231247  \n",
       "3      facebook          20091031060129  \n",
       "4         basic          20091208061105  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x17681490400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "df[\"gender\"] = df['gender'].fillna('M')\n",
    "sns.countplot(data=df, x='gender')\n",
    "plt.xticks(np.arange(4), (\"NaN\", \"Male\", \"Female\", \"Other\"))\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Users gender distribution')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Approx. 45% of users' gender were not presented. And there is no significant difference between female and male users on Airbnb's platform."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Travel Destination Country\n",
    "\n",
    "This is the what we will predict in the test data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x29e7a116da0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='country_destination', data=df)\n",
    "plt.xlabel('Destination Country')\n",
    "plt.ylabel('Number of users')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Nearly 60% of users did not book any destination (NDF). The most booked country is the US (nearly 30% of all users booked US), given all users in the data set are from the US. We can say that users in the dataset are more likely to travel within the US. We will only study users who made at least one reservation, and removing users who did not book any destination."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x176f619b6d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "df_without_NDF = df[df['country_destination']!='NDF']\n",
    "sns.boxplot(y='age' , x='country_destination',data=df_without_NDF)\n",
    "plt.xlabel('Destination Country box plot')\n",
    "plt.ylabel('Age of Users')\n",
    "plt.title('Country destination vs. age')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There were no significant age difference among users who book difference destinations. However, users who booked Great Britain tend to be a little older than users who booked Spain and Portugal."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Users' Signup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x29e0895e4e0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "df_without_NDF = df[df['country_destination']!='NDF']\n",
    "sns.countplot(x='signup_method', data = df_without_NDF)\n",
    "plt.xlabel('Destination Country')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Users sign up method distribution')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Over 70% of all bookers in the data used basic email method to sign up with Airbnb, and less than 30% of bookers used their facebook account to sign up, approx. only 0.26% of the bookers in the data used their Google accounts to sign up."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d2e678668>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='country_destination', data = df_without_NDF, hue = 'signup_method')\n",
    "plt.xlabel('Destination Country')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Users sign up method vs. destinations')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For users who made booking at least once, most of them signed up with Airbnb through basic email method, no matter which country they were travelling to."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d3a0ab780>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='signup_app', data=df_without_NDF)\n",
    "plt.xlabel('Signup app')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Signup app distribution')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Over 85% of all bookers in the data set signed up on Airbnb's website, over 10% of all bookers signed up with iOs. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d3b5134a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='country_destination', data=df_without_NDF, hue='signup_app')\n",
    "plt.xlabel('Destination Country')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Destinatiuon country based on signup app')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "US bookers have more variety of sign up apps than bookers in other countries. To see more clearer, we remove the US."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x17681450588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_without_NDF_US = df_without_NDF[df_without_NDF['country_destination']!='US']\n",
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='country_destination', data=df_without_NDF_US, hue='signup_app')\n",
    "plt.xlabel('Destination Country')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Destinatiuon country based on signup app without the US')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Signing up through Airbnb website is the most common sign up on booking every destination country in the data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Affiliate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d3b56c940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='affiliate_channel', data=df_without_NDF)\n",
    "plt.xlabel('Affiliate channel')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Affiliate channel distribution')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d3d171a58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='country_destination', data=df_without_NDF, hue = 'affiliate_channel')\n",
    "plt.xlabel('Affiliate channel')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Affiliate channel vs country destination')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's remove the US again."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x176823b4ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='country_destination', data=df_without_NDF_US, hue = 'affiliate_channel')\n",
    "plt.xlabel('Affiliate channel')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Affiliate channel vs country destination without the US')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d3d7144a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,6))\n",
    "sns.countplot(x='affiliate_provider', data=df_without_NDF)\n",
    "plt.xlabel('Affiliate provider')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Affiliate provider distribution')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d3bb6a5f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='country_destination', data=df_without_NDF, hue = 'affiliate_provider')\n",
    "plt.xlabel('Affiliate provider')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Affiliate provider vs country destination')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1768fec13c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='country_destination', data=df_without_NDF_US, hue = 'affiliate_provider')\n",
    "plt.xlabel('Affiliate provider')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Affiliate provider vs country destination without the US')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Approx. 65% of bookers signed up directly, without any affiliate program. And over 23% of bookers signed up through Google affiliate program, however, if you remember, there were only 0.26% of bookers signed up with their Google accounts."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### First"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d3b4bde80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='first_affiliate_tracked', data=df_without_NDF)\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('First affiliate tracked distribution')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d3b4bc7b8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,6))\n",
    "sns.countplot(x='first_device_type', data=df_without_NDF)\n",
    "plt.xlabel('First device type')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('First device type distribution')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d3b5ada58>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,6))\n",
    "sns.countplot(x='country_destination', data=df_without_NDF, hue='first_device_type')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('First device type vs. country destination')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Around 60% of bookers use Apple devices. Particularly in the US."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x176f56b4320>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,6))\n",
    "sns.countplot(x='country_destination', data=df_without_NDF_US, hue='first_device_type')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('First device type vs. country destination without the US')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "However, outside of the US, Windows descktop is far more common, in particular, there was little usage difference between Mac desktop and Windows desktop in Canada and Australia."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d3a052c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,6))\n",
    "sns.countplot(x='first_browser', data=df_without_NDF)\n",
    "plt.xlabel('First browser')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('First browser distribution')\n",
    "plt.xticks(rotation=90)\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Almost 30% of bookers in the data used Chrome browser."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Users' Preferred Language"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x29e0b3ce4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='language', data=df_without_NDF)\n",
    "plt.xlabel('language')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Users language distribution')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Vast majority of the bookers' language preference is English, there is no surprise given most of the users in the data set are from the US."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x17690235cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "sns.countplot(x='language', data=df_without_NDF_US)\n",
    "plt.xlabel('language')\n",
    "plt.ylabel('Number of users')\n",
    "plt.title('Users language distribution without the US')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Without the US, English is still the most preferred langauge, interestingly, Chinese is the 2nd most preferred languages for bookers.  "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Dates"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SusanLi\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n",
      "C:\\Users\\SusanLi\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n",
      "C:\\Users\\SusanLi\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:3: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  This is separate from the ipykernel package so we can avoid doing imports until\n",
      "C:\\Users\\SusanLi\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:4: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  after removing the cwd from sys.path.\n",
      "C:\\Users\\SusanLi\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:5: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"\n"
     ]
    }
   ],
   "source": [
    "df_without_NDF['date_account_created'] = pd.to_datetime(df_without_NDF['date_account_created'])\n",
    "df_without_NDF['timestamp_first_active'] = pd.to_datetime((df_without_NDF.timestamp_first_active // 1000000), format='%Y%m%d')\n",
    "# df_without_NDF['date_account_created_day'] = df_without_NDF.date_account_created.dt.weekday_name\n",
    "# df_without_NDF['date_account_created_month'] = df_without_NDF.date_account_created.dt.month\n",
    "# df_without_NDF['date_account_created_year'] = df_without_NDF.date_account_created.dt.year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>affiliate_channel</th>\n",
       "      <th>affiliate_provider</th>\n",
       "      <th>age</th>\n",
       "      <th>country_destination</th>\n",
       "      <th>date_account_created</th>\n",
       "      <th>first_affiliate_tracked</th>\n",
       "      <th>first_browser</th>\n",
       "      <th>first_device_type</th>\n",
       "      <th>gender</th>\n",
       "      <th>id</th>\n",
       "      <th>language</th>\n",
       "      <th>signup_app</th>\n",
       "      <th>signup_flow</th>\n",
       "      <th>signup_method</th>\n",
       "      <th>timestamp_first_active</th>\n",
       "      <th>date_account_created_day</th>\n",
       "      <th>date_account_created_month</th>\n",
       "      <th>date_account_created_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>56.0</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-09-28</td>\n",
       "      <td>untracked</td>\n",
       "      <td>IE</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>4ft3gnwmtx</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>3</td>\n",
       "      <td>basic</td>\n",
       "      <td>2009-06-09</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>9</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>42.0</td>\n",
       "      <td>other</td>\n",
       "      <td>2011-12-05</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Firefox</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>bjjt8pjhuk</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>facebook</td>\n",
       "      <td>2009-10-31</td>\n",
       "      <td>Monday</td>\n",
       "      <td>12</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>41.0</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-09-14</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>M</td>\n",
       "      <td>87mebub9p4</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>basic</td>\n",
       "      <td>2009-12-08</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>9</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>other</td>\n",
       "      <td>other</td>\n",
       "      <td>NaN</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>omg</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>M</td>\n",
       "      <td>osr2jwljor</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>basic</td>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>other</td>\n",
       "      <td>craigslist</td>\n",
       "      <td>46.0</td>\n",
       "      <td>US</td>\n",
       "      <td>2010-01-02</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Safari</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>lsw9q7uk0j</td>\n",
       "      <td>en</td>\n",
       "      <td>Web</td>\n",
       "      <td>0</td>\n",
       "      <td>basic</td>\n",
       "      <td>2010-01-02</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  affiliate_channel affiliate_provider   age country_destination  \\\n",
       "2            direct             direct  56.0                  US   \n",
       "3            direct             direct  42.0               other   \n",
       "4            direct             direct  41.0                  US   \n",
       "5             other              other   NaN                  US   \n",
       "6             other         craigslist  46.0                  US   \n",
       "\n",
       "  date_account_created first_affiliate_tracked first_browser  \\\n",
       "2           2010-09-28               untracked            IE   \n",
       "3           2011-12-05               untracked       Firefox   \n",
       "4           2010-09-14               untracked        Chrome   \n",
       "5           2010-01-01                     omg        Chrome   \n",
       "6           2010-01-02               untracked        Safari   \n",
       "\n",
       "  first_device_type  gender          id language signup_app  signup_flow  \\\n",
       "2   Windows Desktop  FEMALE  4ft3gnwmtx       en        Web            3   \n",
       "3       Mac Desktop  FEMALE  bjjt8pjhuk       en        Web            0   \n",
       "4       Mac Desktop       M  87mebub9p4       en        Web            0   \n",
       "5       Mac Desktop       M  osr2jwljor       en        Web            0   \n",
       "6       Mac Desktop  FEMALE  lsw9q7uk0j       en        Web            0   \n",
       "\n",
       "  signup_method timestamp_first_active date_account_created_day  \\\n",
       "2         basic             2009-06-09                  Tuesday   \n",
       "3      facebook             2009-10-31                   Monday   \n",
       "4         basic             2009-12-08                  Tuesday   \n",
       "5         basic             2010-01-01                   Friday   \n",
       "6         basic             2010-01-02                 Saturday   \n",
       "\n",
       "   date_account_created_month  date_account_created_year  \n",
       "2                           9                       2010  \n",
       "3                          12                       2011  \n",
       "4                           9                       2010  \n",
       "5                           1                       2010  \n",
       "6                           1                       2010  "
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_without_NDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x29e089d1208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "df_without_NDF.date_account_created.value_counts().plot(kind='line', linewidth=1.2)\n",
    "plt.xlabel('Date')\n",
    "plt.title('New account created over time')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x27d2eca6e10>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,6))\n",
    "df_without_NDF.timestamp_first_active.value_counts().plot(kind='line', linewidth=1.2)\n",
    "plt.xlabel('Date')\n",
    "plt.title('First active date over time')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The pattern looks similar between date account created and date first active, as it shoule be. From these two plots, we can see how fast Airbnb has grown in the past a few years."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x29e0c94f4a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "df_2013 = df_without_NDF[df_without_NDF['timestamp_first_active'] > pd.to_datetime(20130101, format='%Y%m%d')]\n",
    "df_2013 = df_2013[df_2013['timestamp_first_active'] < pd.to_datetime(20140101, format='%Y%m%d')]\n",
    "plt.figure(figsize=(12,6))\n",
    "df_2013.timestamp_first_active.value_counts().plot(kind='line', linewidth=2)\n",
    "plt.xlabel('Date')\n",
    "plt.title('First active date 2013')\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When dive into 2013, we see that there were several peak months for Airbnb users such as July, August and October, and December is the least active month for Airbnb users. In addition, it follows a similar pattern, such as peaks and off-peaks at the similar distance."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## User Session Exploration "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There were 135484  unique user IDs in the session data.\n"
     ]
    }
   ],
   "source": [
    "sessions = pd.read_csv('sessions.csv')\n",
    "\n",
    "print(\"There were\", len(sessions.user_id.unique()), \" unique user IDs in the session data.\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are not many features in sessions data set, we can explore them one by one."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "user_id            34496\n",
       "action             79626\n",
       "action_type      1126204\n",
       "action_detail    1126204\n",
       "device_type            0\n",
       "secs_elapsed      136031\n",
       "dtype: int64"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sessions.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>action</th>\n",
       "      <th>action_type</th>\n",
       "      <th>action_detail</th>\n",
       "      <th>device_type</th>\n",
       "      <th>secs_elapsed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>d1mm9tcy42</td>\n",
       "      <td>lookup</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>319.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>d1mm9tcy42</td>\n",
       "      <td>search_results</td>\n",
       "      <td>click</td>\n",
       "      <td>view_search_results</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>67753.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>d1mm9tcy42</td>\n",
       "      <td>lookup</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>301.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>d1mm9tcy42</td>\n",
       "      <td>search_results</td>\n",
       "      <td>click</td>\n",
       "      <td>view_search_results</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>22141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>d1mm9tcy42</td>\n",
       "      <td>lookup</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>435.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id          action action_type        action_detail  \\\n",
       "0  d1mm9tcy42          lookup         NaN                  NaN   \n",
       "1  d1mm9tcy42  search_results       click  view_search_results   \n",
       "2  d1mm9tcy42          lookup         NaN                  NaN   \n",
       "3  d1mm9tcy42  search_results       click  view_search_results   \n",
       "4  d1mm9tcy42          lookup         NaN                  NaN   \n",
       "\n",
       "       device_type  secs_elapsed  \n",
       "0  Windows Desktop         319.0  \n",
       "1  Windows Desktop       67753.0  \n",
       "2  Windows Desktop         301.0  \n",
       "3  Windows Desktop       22141.0  \n",
       "4  Windows Desktop         435.0  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sessions.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Action Type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, 'click', 'data', 'view', 'submit', 'message_post',\n",
       "       '-unknown-', 'booking_request', 'partner_callback',\n",
       "       'booking_response', 'modify'], dtype=object)"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sessions.action_type.unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We have \"NaN\" and \"unknown\" in the action type. So we will change \"unknown\" to \"NaN\"."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "sessions.action_type.replace('-unknown-', np.nan, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "view                3560902\n",
       "data                2103770\n",
       "click               1996183\n",
       "submit               623357\n",
       "message_post          87103\n",
       "partner_callback      19132\n",
       "booking_request       18773\n",
       "modify                 1139\n",
       "booking_response          4\n",
       "Name: action_type, dtype: int64"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sessions.action_type.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Action"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "show                     2768278\n",
       "index                     843699\n",
       "search_results            725226\n",
       "personalize               706824\n",
       "search                    536057\n",
       "ajax_refresh_subtotal     487744\n",
       "update                    365130\n",
       "similar_listings          364624\n",
       "social_connections        339000\n",
       "reviews                   320591\n",
       "Name: action, dtype: int64"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sessions.action.value_counts().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Action detail"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 198,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "view_search_results            1776885\n",
       "p3                             1376550\n",
       "-unknown-                      1031141\n",
       "wishlist_content_update         706824\n",
       "user_profile                    656839\n",
       "change_trip_characteristics     487744\n",
       "similar_listings                364624\n",
       "user_social_connections         336799\n",
       "update_listing                  269779\n",
       "listing_reviews                 269021\n",
       "Name: action_detail, dtype: int64"
      ]
     },
     "execution_count": 198,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sessions.action_detail.value_counts().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Device type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 202,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x20f000d9748>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(18,6))\n",
    "sns.countplot(x='device_type', data=sessions)\n",
    "plt.xlabel('device type')\n",
    "plt.ylabel('Number of sessions')\n",
    "plt.title('device type distribution')\n",
    "plt.xticks(rotation=90)\n",
    "sns.despine()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This affirms the previous discovery about users. The most common device type among Airbnb users are Apple products."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Sessions of Users who had made bookings\n",
    "\n",
    "From the previous analysis, we know which users had made bookings through Airbnb, so we want to explore these bookers session data. Are they different with non-bookers?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 205,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>date_account_created</th>\n",
       "      <th>timestamp_first_active</th>\n",
       "      <th>gender</th>\n",
       "      <th>age</th>\n",
       "      <th>signup_method</th>\n",
       "      <th>signup_flow</th>\n",
       "      <th>language</th>\n",
       "      <th>affiliate_channel</th>\n",
       "      <th>affiliate_provider</th>\n",
       "      <th>first_affiliate_tracked</th>\n",
       "      <th>signup_app</th>\n",
       "      <th>first_device_type</th>\n",
       "      <th>first_browser</th>\n",
       "      <th>country_destination</th>\n",
       "      <th>date_account_created_day</th>\n",
       "      <th>date_account_created_month</th>\n",
       "      <th>date_account_created_year</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>4ft3gnwmtx</td>\n",
       "      <td>2010-09-28</td>\n",
       "      <td>2009-06-09</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>56.0</td>\n",
       "      <td>basic</td>\n",
       "      <td>3</td>\n",
       "      <td>en</td>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Web</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>IE</td>\n",
       "      <td>US</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>9</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>bjjt8pjhuk</td>\n",
       "      <td>2011-12-05</td>\n",
       "      <td>2009-10-31</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>42.0</td>\n",
       "      <td>facebook</td>\n",
       "      <td>0</td>\n",
       "      <td>en</td>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Web</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>Firefox</td>\n",
       "      <td>other</td>\n",
       "      <td>Monday</td>\n",
       "      <td>12</td>\n",
       "      <td>2011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>87mebub9p4</td>\n",
       "      <td>2010-09-14</td>\n",
       "      <td>2009-12-08</td>\n",
       "      <td>M</td>\n",
       "      <td>41.0</td>\n",
       "      <td>basic</td>\n",
       "      <td>0</td>\n",
       "      <td>en</td>\n",
       "      <td>direct</td>\n",
       "      <td>direct</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Web</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>US</td>\n",
       "      <td>Tuesday</td>\n",
       "      <td>9</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>osr2jwljor</td>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>M</td>\n",
       "      <td>NaN</td>\n",
       "      <td>basic</td>\n",
       "      <td>0</td>\n",
       "      <td>en</td>\n",
       "      <td>other</td>\n",
       "      <td>other</td>\n",
       "      <td>omg</td>\n",
       "      <td>Web</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>Chrome</td>\n",
       "      <td>US</td>\n",
       "      <td>Friday</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>lsw9q7uk0j</td>\n",
       "      <td>2010-01-02</td>\n",
       "      <td>2010-01-02</td>\n",
       "      <td>FEMALE</td>\n",
       "      <td>46.0</td>\n",
       "      <td>basic</td>\n",
       "      <td>0</td>\n",
       "      <td>en</td>\n",
       "      <td>other</td>\n",
       "      <td>craigslist</td>\n",
       "      <td>untracked</td>\n",
       "      <td>Web</td>\n",
       "      <td>Mac Desktop</td>\n",
       "      <td>Safari</td>\n",
       "      <td>US</td>\n",
       "      <td>Saturday</td>\n",
       "      <td>1</td>\n",
       "      <td>2010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id date_account_created timestamp_first_active  gender   age  \\\n",
       "2  4ft3gnwmtx           2010-09-28             2009-06-09  FEMALE  56.0   \n",
       "3  bjjt8pjhuk           2011-12-05             2009-10-31  FEMALE  42.0   \n",
       "4  87mebub9p4           2010-09-14             2009-12-08       M  41.0   \n",
       "5  osr2jwljor           2010-01-01             2010-01-01       M   NaN   \n",
       "6  lsw9q7uk0j           2010-01-02             2010-01-02  FEMALE  46.0   \n",
       "\n",
       "  signup_method  signup_flow language affiliate_channel affiliate_provider  \\\n",
       "2         basic            3       en            direct             direct   \n",
       "3      facebook            0       en            direct             direct   \n",
       "4         basic            0       en            direct             direct   \n",
       "5         basic            0       en             other              other   \n",
       "6         basic            0       en             other         craigslist   \n",
       "\n",
       "  first_affiliate_tracked signup_app first_device_type first_browser  \\\n",
       "2               untracked        Web   Windows Desktop            IE   \n",
       "3               untracked        Web       Mac Desktop       Firefox   \n",
       "4               untracked        Web       Mac Desktop        Chrome   \n",
       "5                     omg        Web       Mac Desktop        Chrome   \n",
       "6               untracked        Web       Mac Desktop        Safari   \n",
       "\n",
       "  country_destination date_account_created_day  date_account_created_month  \\\n",
       "2                  US                  Tuesday                           9   \n",
       "3               other                   Monday                          12   \n",
       "4                  US                  Tuesday                           9   \n",
       "5                  US                   Friday                           1   \n",
       "6                  US                 Saturday                           1   \n",
       "\n",
       "   date_account_created_year  \n",
       "2                       2010  \n",
       "3                       2011  \n",
       "4                       2010  \n",
       "5                       2010  \n",
       "6                       2010  "
      ]
     },
     "execution_count": 205,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_without_NDF.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 206,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>action</th>\n",
       "      <th>action_type</th>\n",
       "      <th>action_detail</th>\n",
       "      <th>device_type</th>\n",
       "      <th>secs_elapsed</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>d1mm9tcy42</td>\n",
       "      <td>lookup</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>319.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>d1mm9tcy42</td>\n",
       "      <td>search_results</td>\n",
       "      <td>click</td>\n",
       "      <td>view_search_results</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>67753.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>d1mm9tcy42</td>\n",
       "      <td>lookup</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>301.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>d1mm9tcy42</td>\n",
       "      <td>search_results</td>\n",
       "      <td>click</td>\n",
       "      <td>view_search_results</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>22141.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>d1mm9tcy42</td>\n",
       "      <td>lookup</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Windows Desktop</td>\n",
       "      <td>435.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      user_id          action action_type        action_detail  \\\n",
       "0  d1mm9tcy42          lookup         NaN                  NaN   \n",
       "1  d1mm9tcy42  search_results       click  view_search_results   \n",
       "2  d1mm9tcy42          lookup         NaN                  NaN   \n",
       "3  d1mm9tcy42  search_results       click  view_search_results   \n",
       "4  d1mm9tcy42          lookup         NaN                  NaN   \n",
       "\n",
       "       device_type  secs_elapsed  \n",
       "0  Windows Desktop         319.0  \n",
       "1  Windows Desktop       67753.0  \n",
       "2  Windows Desktop         301.0  \n",
       "3  Windows Desktop       22141.0  \n",
       "4  Windows Desktop         435.0  "
      ]
     },
     "execution_count": 206,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sessions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 207,
   "metadata": {},
   "outputs": [],
   "source": [
    "booker_session = pd.merge(df_without_NDF, sessions, how = 'left', left_on = 'id', right_on = 'user_id')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bookers action type"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 209,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "view                748404\n",
       "data                516182\n",
       "click               481757\n",
       "submit              138407\n",
       "message_post         32299\n",
       "booking_request       9081\n",
       "partner_callback      3798\n",
       "booking_response         1\n",
       "Name: action_type, dtype: int64"
      ]
     },
     "execution_count": 209,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "booker_session.action_type.value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Bookers top actions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 210,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "show                     547951\n",
       "personalize              211836\n",
       "index                    209351\n",
       "search_results           192670\n",
       "ajax_refresh_subtotal    157051\n",
       "similar_listings         147387\n",
       "search                    66580\n",
       "update                    63860\n",
       "lookup                    62281\n",
       "social_connections        47225\n",
       "Name: action, dtype: int64"
      ]
     },
     "execution_count": 210,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "booker_session.action.value_counts().head(10)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Unfortunately, there was no significant difference in actions between bookers and all users."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Data Preprocessing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [],
   "source": [
    "train_users = pd.read_csv('train_users_2.csv')\n",
    "test_users = pd.read_csv('test_users.csv')\n",
    "df = pd.concat((train_users, test_users), axis=0, ignore_index=True)\n",
    "df.drop('date_first_booking', axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Date time features\n",
    "\n",
    "Cast date time column to property date time format, Split dates into day, week, month, year, Get the difference(time lag) between the date in which the account was created and when it was first active."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "df['date_account_created'] = pd.to_datetime(df['date_account_created'])\n",
    "df['timestamp_first_active'] = pd.to_datetime((df.timestamp_first_active // 1000000), format='%Y%m%d')\n",
    "df['weekday_account_created'] = df.date_account_created.dt.weekday_name\n",
    "df['day_account_created'] = df.date_account_created.dt.day\n",
    "df['month_account_created'] = df.date_account_created.dt.month\n",
    "df['year_account_created'] = df.date_account_created.dt.year\n",
    "df['weekday_first_active'] = df.timestamp_first_active.dt.weekday_name\n",
    "df['day_first_active'] = df.timestamp_first_active.dt.day\n",
    "df['month_first_active'] = df.timestamp_first_active.dt.month\n",
    "df['year_first_active'] = df.timestamp_first_active.dt.year\n",
    "df['time_lag'] = (df['date_account_created'] - df['timestamp_first_active'])\n",
    "df['time_lag'] = df['time_lag'].astype(pd.Timedelta).apply(lambda l: l.days)\n",
    "\n",
    "cols_to_drop = ['date_account_created', 'timestamp_first_active']\n",
    "df.drop(cols_to_drop, axis=1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['affiliate_channel', 'affiliate_provider', 'age', 'country_destination',\n",
       "       'first_affiliate_tracked', 'first_browser', 'first_device_type',\n",
       "       'gender', 'id', 'language', 'signup_app', 'signup_flow',\n",
       "       'signup_method', 'weekday_account_created', 'day_account_created',\n",
       "       'month_account_created', 'year_account_created', 'weekday_first_active',\n",
       "       'day_first_active', 'month_first_active', 'year_first_active',\n",
       "       'time_lag'],\n",
       "      dtype='object')"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Age features"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Convert year to age, set limits to age, and fill NaNs with -1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "df_with_year = df['age'] > 1000\n",
    "df.loc[df_with_year, 'age'] = 2015 - df.loc[df_with_year, 'age']\n",
    "df.loc[df.age > 95, 'age'] = np.nan\n",
    "df.loc[df.age < 16, 'age'] = np.nan\n",
    "df['age'].fillna(-1, inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### User session action features\n",
    "\n",
    "Group by user_id, count the number of times an action, action type and action detail is made by each user. Doing groupby.agg(len) is roughly twice as fast as groupby.size(). Therefore, I am using groupby.agg(len). For device type, we group by user_id, sum up total secs_elapses for each user. Finally, we add a new column named \"most_used_device\" for each user most used device."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "sessions = pd.read_csv('sessions.csv')\n",
    "sessions.rename(columns={'user_id': 'id'}, inplace=True)\n",
    "action_count = sessions.groupby(['id', 'action'])['secs_elapsed'].agg(len).unstack()\n",
    "action_type_count = sessions.groupby(['id', 'action_type'])['secs_elapsed'].agg(len).unstack()\n",
    "action_detail_count = sessions.groupby(['id', 'action_detail'])['secs_elapsed'].agg(len).unstack()\n",
    "device_type_sum = sessions.groupby(['id', 'device_type'])['secs_elapsed'].agg(sum).unstack()\n",
    "\n",
    "sessions_data = pd.concat([action_count, action_type_count, action_detail_count, device_type_sum],axis=1)\n",
    "sessions_data.columns = sessions_data.columns.map(lambda x: str(x) + '_count')\n",
    "\n",
    "# Most used device\n",
    "sessions_data['most_used_device'] = sessions.groupby('id')['device_type'].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There were 10567737 recorded sessions to which there were 135483 unique users.\n"
     ]
    }
   ],
   "source": [
    "print('There were', sessions.shape[0], 'recorded sessions to which there were', sessions.id.nunique(), 'unique users.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [],
   "source": [
    "sessions_data.index.names = ['id']\n",
    "sessions_data.reset_index(inplace=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### User sessions secs_elapsed features\n",
    "\n",
    "We will extract information from secs_elapsed feature for each user, such as sum, mean, min, max, median, variance, if the sum of secs_elapsed is greater than 86,400 second, we consider day_pause, if the sum of secs_elapsed is greater than 300,000 seconds, we consider it is a long pause, and if the sum of secs_elapsed is shorter than 3,600 seconds, we consider it is a short pause."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\SusanLi\\AppData\\Local\\Continuum\\anaconda3\\lib\\site-packages\\ipykernel_launcher.py:15: FutureWarning: using a dict on a Series for aggregation\n",
      "is deprecated and will be removed in a future version\n",
      "  from ipykernel import kernelapp as app\n"
     ]
    }
   ],
   "source": [
    "secs_elapsed = sessions.groupby('id')['secs_elapsed']\n",
    "\n",
    "secs_elapsed = secs_elapsed.agg(\n",
    "    {\n",
    "        'secs_elapsed_sum': np.sum,\n",
    "        'secs_elapsed_mean': np.mean,\n",
    "        'secs_elapsed_min': np.min,\n",
    "        'secs_elapsed_max': np.max,\n",
    "        'secs_elapsed_median': np.median,\n",
    "        'secs_elapsed_std': np.std,\n",
    "        'secs_elapsed_var': np.var,\n",
    "        'day_pauses': lambda x: (x > 86400).sum(),\n",
    "        'long_pauses': lambda x: (x > 300000).sum(),\n",
    "        'short_pauses': lambda x: (x < 3600).sum(),\n",
    "        'session_length' : np.count_nonzero\n",
    "    }\n",
    ")\n",
    "secs_elapsed.reset_index(inplace=True)\n",
    "sessions_secs_elapsed = pd.merge(sessions_data, secs_elapsed, on='id', how='left')\n",
    "df = pd.merge(df, sessions_secs_elapsed, on='id', how = 'left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>id</th>\n",
       "      <th>secs_elapsed_sum</th>\n",
       "      <th>secs_elapsed_mean</th>\n",
       "      <th>secs_elapsed_min</th>\n",
       "      <th>secs_elapsed_max</th>\n",
       "      <th>secs_elapsed_median</th>\n",
       "      <th>secs_elapsed_std</th>\n",
       "      <th>secs_elapsed_var</th>\n",
       "      <th>day_pauses</th>\n",
       "      <th>long_pauses</th>\n",
       "      <th>short_pauses</th>\n",
       "      <th>session_length</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>00023iyk9l</td>\n",
       "      <td>867896.0</td>\n",
       "      <td>22253.743590</td>\n",
       "      <td>0.0</td>\n",
       "      <td>567165.0</td>\n",
       "      <td>850.0</td>\n",
       "      <td>92242.561900</td>\n",
       "      <td>8.508690e+09</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>29.0</td>\n",
       "      <td>39.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0010k6l0om</td>\n",
       "      <td>586543.0</td>\n",
       "      <td>9460.370968</td>\n",
       "      <td>3.0</td>\n",
       "      <td>127898.0</td>\n",
       "      <td>948.5</td>\n",
       "      <td>22751.227918</td>\n",
       "      <td>5.176184e+08</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>46.0</td>\n",
       "      <td>63.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>001wyh0pz8</td>\n",
       "      <td>282965.0</td>\n",
       "      <td>3179.382022</td>\n",
       "      <td>35.0</td>\n",
       "      <td>50548.0</td>\n",
       "      <td>1105.0</td>\n",
       "      <td>6569.648182</td>\n",
       "      <td>4.316028e+07</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>71.0</td>\n",
       "      <td>90.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0028jgx1x1</td>\n",
       "      <td>297010.0</td>\n",
       "      <td>9900.333333</td>\n",
       "      <td>3.0</td>\n",
       "      <td>84636.0</td>\n",
       "      <td>1614.0</td>\n",
       "      <td>18004.964337</td>\n",
       "      <td>3.241787e+08</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>31.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>002qnbzfs5</td>\n",
       "      <td>6487080.0</td>\n",
       "      <td>8232.335025</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1418284.0</td>\n",
       "      <td>498.0</td>\n",
       "      <td>58110.646170</td>\n",
       "      <td>3.376847e+09</td>\n",
       "      <td>13.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>602.0</td>\n",
       "      <td>787.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           id  secs_elapsed_sum  secs_elapsed_mean  secs_elapsed_min  \\\n",
       "0  00023iyk9l          867896.0       22253.743590               0.0   \n",
       "1  0010k6l0om          586543.0        9460.370968               3.0   \n",
       "2  001wyh0pz8          282965.0        3179.382022              35.0   \n",
       "3  0028jgx1x1          297010.0        9900.333333               3.0   \n",
       "4  002qnbzfs5         6487080.0        8232.335025               0.0   \n",
       "\n",
       "   secs_elapsed_max  secs_elapsed_median  secs_elapsed_std  secs_elapsed_var  \\\n",
       "0          567165.0                850.0      92242.561900      8.508690e+09   \n",
       "1          127898.0                948.5      22751.227918      5.176184e+08   \n",
       "2           50548.0               1105.0       6569.648182      4.316028e+07   \n",
       "3           84636.0               1614.0      18004.964337      3.241787e+08   \n",
       "4         1418284.0                498.0      58110.646170      3.376847e+09   \n",
       "\n",
       "   day_pauses  long_pauses  short_pauses  session_length  \n",
       "0         2.0          1.0          29.0            39.0  \n",
       "1         2.0          0.0          46.0            63.0  \n",
       "2         0.0          0.0          71.0            90.0  \n",
       "3         0.0          0.0          17.0            31.0  \n",
       "4        13.0          3.0         602.0           787.0  "
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "secs_elapsed.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "There are 275547 users from the entire user data set that have session information.\n"
     ]
    }
   ],
   "source": [
    "print('There are', df.id.nunique(), 'users from the entire user data set that have session information.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Encoding categorical features "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "categorical_features = ['gender', 'signup_method', 'signup_flow', 'language','affiliate_channel', 'affiliate_provider', 'first_affiliate_tracked', 'signup_app', 'first_device_type', 'first_browser', 'most_used_device', 'weekday_account_created', 'weekday_first_active']\n",
    "df = pd.get_dummies(df, columns=categorical_features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index('id', inplace=True)\n",
    "train_df = df.loc[train_users['id']]\n",
    "test_df = df.loc[test_users['id']].drop('country_destination', axis=1)\n",
    "train_df.reset_index(inplace=True)\n",
    "test_df.reset_index(inplace=True)\n",
    "train_df.fillna(-1, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.preprocessing import LabelEncoder\n",
    "\n",
    "y_train = train_df['country_destination']\n",
    "train_df.drop(['country_destination', 'id'], axis=1, inplace=True)\n",
    "x_train = train_df.values\n",
    "\n",
    "label_encoder = LabelEncoder()\n",
    "encoded_y_train = label_encoder.fit_transform(y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xgboost as xgb\n",
    "\n",
    "xgtrain = xgb.DMatrix(x_train, label=encoded_y_train)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Normalized Discounted Cumulative Gain (NDCG)\n",
    "\n",
    "The evaluation metric is NDCG @k where k=5. So we select top 5 then get the average."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [],
   "source": [
    "def ndcg_score(preds, dtrain):\n",
    "    labels = dtrain.get_label()\n",
    "    top = []\n",
    "\n",
    "    for i in range(preds.shape[0]):\n",
    "        top.append(np.argsort(preds[i])[::-1][:5])\n",
    "\n",
    "    mat = np.reshape(np.repeat(labels,np.shape(top)[1]) == np.array(top).ravel(),np.array(top).shape).astype(int)\n",
    "    score = np.mean(np.sum(mat/np.log2(np.arange(2, mat.shape[1] + 2)),axis = 1))\n",
    "    return 'ndcg', score"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We set the general parameters, tree booster parameters and learning task parameters as follows, and our evaluation metrics is mlogloss (Multiclass logloss). The detailed guide on how to set Xgboost parameters can be found on its official website. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>test-mlogloss-mean</th>\n",
       "      <th>test-mlogloss-std</th>\n",
       "      <th>test-ndcg-mean</th>\n",
       "      <th>test-ndcg-std</th>\n",
       "      <th>train-mlogloss-mean</th>\n",
       "      <th>train-mlogloss-std</th>\n",
       "      <th>train-ndcg-mean</th>\n",
       "      <th>train-ndcg-std</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.217951</td>\n",
       "      <td>0.006288</td>\n",
       "      <td>0.827582</td>\n",
       "      <td>0.000760</td>\n",
       "      <td>1.169001</td>\n",
       "      <td>0.001019</td>\n",
       "      <td>0.836515</td>\n",
       "      <td>0.000507</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1.461221</td>\n",
       "      <td>0.011611</td>\n",
       "      <td>0.746653</td>\n",
       "      <td>0.002862</td>\n",
       "      <td>1.355022</td>\n",
       "      <td>0.016621</td>\n",
       "      <td>0.767310</td>\n",
       "      <td>0.001826</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.173415</td>\n",
       "      <td>0.019579</td>\n",
       "      <td>0.820226</td>\n",
       "      <td>0.000849</td>\n",
       "      <td>1.042072</td>\n",
       "      <td>0.030455</td>\n",
       "      <td>0.846295</td>\n",
       "      <td>0.001097</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2.304768</td>\n",
       "      <td>0.920188</td>\n",
       "      <td>0.773338</td>\n",
       "      <td>0.014774</td>\n",
       "      <td>2.147041</td>\n",
       "      <td>0.967472</td>\n",
       "      <td>0.805529</td>\n",
       "      <td>0.016622</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>1.393931</td>\n",
       "      <td>0.098129</td>\n",
       "      <td>0.817316</td>\n",
       "      <td>0.000830</td>\n",
       "      <td>1.196478</td>\n",
       "      <td>0.114288</td>\n",
       "      <td>0.853830</td>\n",
       "      <td>0.001706</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   test-mlogloss-mean  test-mlogloss-std  test-ndcg-mean  test-ndcg-std  \\\n",
       "0            1.217951           0.006288        0.827582       0.000760   \n",
       "1            1.461221           0.011611        0.746653       0.002862   \n",
       "2            1.173415           0.019579        0.820226       0.000849   \n",
       "3            2.304768           0.920188        0.773338       0.014774   \n",
       "4            1.393931           0.098129        0.817316       0.000830   \n",
       "\n",
       "   train-mlogloss-mean  train-mlogloss-std  train-ndcg-mean  train-ndcg-std  \n",
       "0             1.169001            0.001019         0.836515        0.000507  \n",
       "1             1.355022            0.016621         0.767310        0.001826  \n",
       "2             1.042072            0.030455         0.846295        0.001097  \n",
       "3             2.147041            0.967472         0.805529        0.016622  \n",
       "4             1.196478            0.114288         0.853830        0.001706  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "param = {\n",
    "    'max_depth': 10,\n",
    "    'learning_rate': 1,\n",
    "    'n_estimators': 5,\n",
    "    'objective': 'multi:softprob',\n",
    "    'num_class': 12,\n",
    "    'gamma': 0,\n",
    "    'min_child_weight': 1,\n",
    "    'max_delta_step': 0,\n",
    "    'subsample': 1,\n",
    "    'colsample_bytree': 1,\n",
    "    'colsample_bylevel': 1,\n",
    "    'reg_alpha': 0,\n",
    "    'reg_lambda': 1,\n",
    "    'scale_pos_weight': 1,\n",
    "    'base_score': 0.5,\n",
    "    'missing': None,\n",
    "    'silent': True,\n",
    "    'nthread': 4,\n",
    "    'seed': 42\n",
    "}\n",
    "# Do cross validation\n",
    "num_round = 5\n",
    "xgb.cv(param, xgtrain, num_boost_round=num_round, metrics=['mlogloss'], feval=ndcg_score)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "From the above script, the highest average test NDCG score we have achieved is 0.827582."
   ]
  }
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